A collaborative study was initiated in 2013 and uses a chronic stress model of abdominal pain in rats to generate peripheral and tissue specific whole-genome gene expression data to complement parallel data collected from human patients with chronic GI symptoms (specifically irritable bowel syndrome) enrolled in clinical protocols. Whole genome gene expression data have been collected on both blood and GI tissue samples and data analysis is in progress. Subsequent studies will elucidate the mechanism(s) underlying altered expression of the biomarkers and correlate with the pathophysiological significance. This is a parallel murine model study of chronic abdominal pain (CAP) and provides an experimental platform, where variables are well controlled for, to test a number of predictions resulting from the gene expression analysis. This research will link the results from peripheral gene expression to the specific tissues of interest and is an important step in validating diagnostic significance of peripheral gene expression profiles and to demonstrate vertical integration of data in the model. The integration of the results of this study with the results from our clinical protocols, and the resulting collaboration, may have real implications for the diagnosis and treatment of patients with chronic digestive disorders. Rats are stressed using a chronic intermittent water avoidance stress model. Stressed animals exhibit visceral hypersensitivity and altered colonic epithelial barrier function. Epigenetic changes to pain pathways and increased paracellular permeability in the colon have been identified and characterized in these animals. Peripheral blood, colonic mucosa and dorsal root ganglia which innervate the viscera are harvested from stressed and control animals for mRNA and miRNA profiling using microarray technology. Traditional statistical data analysis has been applied to the data and is being compared to the results of a novel bioinformatics approach, under development with collaborators. The novel approach relying on techniques and algorithms used in evolutionary biology has yielded consistent results between biological replicates of the experiment, as well as a combined analysis and shows good potential for integrating both whole blood RNA and colon mucosal RNA expression data into a single analysis which summarizes possible relationships between gene expression in the two different tissue types. Additionally, DNA isolated from the colonic mucosa has been used to characterize the colonic mucosa adherent microbiome in the study animals using next generation sequencing of the v3-4 hyper-variable regions of the bacterial 16S region. Data collection has been completed and the data analyses is underway. These data will further be integrated into the novel bioinformatics pipeline to explore the potential for additional vertical integration of data types into a single analysis.